Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

The present study investigated Haematological changes in Mesopotamichthys sharpeyi, as well as determination genotoxic effects of cadmium chloride on bunni fish by using 120 fingerlings, fish were distributed randomly into four treatments in addition to control group. Fish in first group treated (T1) with cadmium 0.093mg/L with changing water and added cadmium continuously, fish in the second group treated (T2) with cadmium 0.093mg/L with changing water without adding cadmium, third treatment (T3) with cadmium 0.046mg/L with changing water and adding cadmium continuously, and fourth treatment (T4) with cadmium 0.046mg/L with changing water without adding cadmium. Results of blood picture in T1 and T3 showed a significant reduction in red bl

This work is concerned with the design and performance evaluation of a shell and double concentric tubes heat exchanger using Solid Works and ANSY (Computational Fluid Dynamics).

Computational fluid dynamics technique which is a computer-based analysis is used to simulate the heat exchanger involving fluid flow, heat transfer. CFD resolve the entire heat exchanger in discrete elements to find: (1) the temperature gradients, (2) pressure distribution, and (3) velocity vectors.  The RNG k-ε model of turbulence is used to determining the accurate results from CFD.

The heat exchanger design for this work consisted of a shell and eight double concentric tubes. The number of inlets are three and that of o

 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on

the behavior of the first-order black and gray solitons propagtedin optical fiber in the presence of frequency chirp is studied analytically and numerically results show that phase profile of black solitons changes abruptly

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

By driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign   and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root      gives invertible model and when the sign is negative means the root      gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when

The current report dealt with the effect of pesticides on the ecosystem through their impact on soil, water, and microorganisms and their impact on human health. As well as this study dealt with the biodegradation process of pesticides and the organisms involved in this process, even some previous studies proved that Bacillus spp. And Pseudomonas sp. Bacteria is the most efficient in the biodegradation of pesticides, at the same time, other previous studies dealt with the environmental factors that affect the biodegradation process of pesticides. It proved that each of the incubation periods, pH, and temperature have different effects on biodegradation. Most of the studies indicated that the best incubation period for biodegradation is 7-8